The overall goal of this research is the development of improved methods for the analysis of nuclear magnetic resonance (NMR) relaxation data in terms of molecular motion. It is clear that dynamics play a significant role in protein-ligand and protein-protein interactions, such as those which occur in drug binding and cellular signaling pathways, and NMR is a unique and powerful tool for the study of such motion. However, the extraction of dynamic information from raw NMR data is a complex multi- step process which involves a number of assumptions and approximations, making a realistic assessment of the uncertainty in the extracted parameters non-trivial. In addition, some potential sources of error associated with the quantitative description of the overall tumbling motion of the protein are commonly neglected by current approaches due to the use of inadequate statistical methodology. This could result in a significant underestimate of the true uncertainties in the parameters describing the motion. This research will examine the range of validity of current approaches, develop the methodology needed to correctly incorporate these sources of error, and investigate optimal data collection strategies. The methods developed will be implemented in a user-friendly software package for the practical analysis of NMR relaxation data.